Evaluasi Algoritma Machine Learning untuk Klasifikasi dan Prediksi Penggunaan Lahan by Fajar Nugraha, Dwi Putro Tejo Baskoro, Suria Darma Tarigan

“…This study aimed to evaluate machine learning algorithms in land use classification and prediction and analyzed land use change from 2002 to 2032. …”
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Regulating neural data processing in the age of BCIs: Ethical concerns and legal approaches by Hong Yang, Li Jiang

“…Brain–computer interfaces (BCIs) have seen increasingly fast growth under the help from AI, algorithms, and cloud computing. While providing great benefits for both medical and educational purposes, BCIs involve processing of neural data which are uniquely sensitive due to their most intimate nature, posing unique risks and ethical concerns especially related to privacy and safe control of our neural data. …”
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Distinguishing novel coronavirus influenza A virus pneumonia with CT radiomics and clinical features by Lianyu Sui, Huan Meng, Jianing Wang, Wei Yang, Lulu Yang, Xudan Chen, Liyong Zhuo, Lihong Xing, Yu Zhang, Jingjing Cui, Xiaoping Yin

“…Firstly, voxel-based gray-level discretization (binWidth = 25) and Z-Score normalization were applied to preprocess the patient's ROI and normalize the extracted features. Then, the most predictive radiomic features were selected and their corresponding coefficients were evaluated using the correlation coefficient algorithm and the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. …”
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Cell Outage Detection and Compensation in Two-Tier Heterogeneous Networks by Wenqian Xue, Hengzhi Zhang, Yong Li, Dong Liang, Mugen Peng

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Analysis of IoT-Collected Radish Growth Data Using Deep Neural Networks by Ivan P. Malashin, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

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Investigating the Role of Code Smells in Preventive Maintenance by Junaid Ali Reshi, Satwinder Singh

“…Code smells, which are indicators of the software quality have not been put to an extensive study for as to determine their role in the prediction of defects in the software. This study aims to investigate the role of code smells in prediction of non-faulty classes. …”
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Резолюция Экспертного совета «Диагностика и лечение больных со сладжем в желчном пузыре» by V. T. Ivashkin, Alexey V. Okhlobystin, Dmitry S. Bordin, M. F. Osipenko, E. Ya. Seleznyova, Yu. O. Shulpekova, S. R. Abdulkhakov, O. P. Alexseyeva, I. G. Bakulin, L. G. Vologjhanina, V. B. Grinevich, N. V. Bakulina, T. A. Kolesova, N. V. Korochanskaya, I. V. Putintseva, A. S. Sarsenbayeva, N. S. Yazenok

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Analysis of Factors Affecting the Success of Sustainable Development Projects with the Help of Machine Learning Tools by Zhi-Jun Chen, Tsung-Shun Hsieh, Seyed Mehdi Mousavi Davoudi

“…The study’s results reveal that employing machine learning tools and algorithms to create a link between project success factors and criteria and prediction can bring multiple advantages, including high accuracy, ease of use, and inference for decision-making. …”
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Novel Condition Monitoring Method for Wind Turbines Based on the Adaptive Multivariate Control Charts and SCADA Data by Qinkai Han, Zhentang Wang, Tao Hu

“…After comparing the regression accuracy of several popular algorithms in the MRA, the random forest is adopted for feature selection and regression prediction. …”
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What Strategy Central Nervous System Uses to Perform a Movement Balanced? Biomechatronical Simulation of Human Lifting by Ali Leylavi Shoushtari

“…The results show that the simulated postures are normal and the predicted motion is performed completely balanced.…”
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Bike-Sharing Static Rebalancing by Considering the Collection of Bicycles in Need of Repair by Sheng Zhang, Guanhua Xiang, Zhongxiang Huang

“…The effectiveness of the algorithms was verified by a detailed numerical example.…”
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Efficient Learning of Long-Range and Equivariant Quantum Systems by Štěpán Šmíd, Roberto Bondesan

“…Recent works have studied the task of predicting the ground state expectation value of sums of geometrically local observables by learning from data. …”
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Cost-sensitive regression learning on small dataset through intra-cluster product favoured feature selection by Fangfang Xu, Huan Zhao, Weihua Zhou, Yun Zhou

“…Massive regression and forecasting tasks are generally cost-sensitive regression learning problems with asymmetric costs between over-prediction and under-prediction. However, existing classic methods, such as clustering and feature selection, are subject to difficulties in dealing with small datasets. …”
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Understanding HLA-DQ in renal transplantation: a mini-review by Rajdeep Das, Neil S. Greenspan

“…Traditional serological or low-resolution typing often misclassifies mismatches, leading to inaccuracies in assessing immunogenicity and predicting outcomes. Emerging molecular mismatch algorithms refine immunogenicity assessments by analyzing amino acid differences and structural interactions. …”
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Improving the Solution of Least Squares Support Vector Machines with Application to a Blast Furnace System by Ling Jian, Shuqian Shen, Yunquan Song

“…To heel, the LS-SVM based on MINRES method is used to track a practical problem originated from blast furnace iron-making process: changing trend prediction of silicon content in hot metal. The MINRES method-based LS-SVM can effectively perform feature reduction and model selection simultaneously, so it is a practical tool for the silicon trend prediction task.…”
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Autoregressive integrated moving average model–based secure data aggregation for wireless sensor networks by Hongtao Song, Shanshan Sui, Qilong Han, Hui Zhang, Zaiqiang Yang

“…We leverage the autoregressive integrated moving average model to predict the data volume in sensor nodes, and update and synchronize the model as needed. …”
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On PTV definition for glioblastoma based on fiber tracking of diffusion tensor imaging data. by Barbara Witulla, Nicole Goerig, Florian Putz, Benjamin Frey, Tobias Engelhorn, Arnd Dörfler, Michael Uder, Rainer Fietkau, Christoph Bert, Frederik Bernd Laun

“…It depended strongly on the used tracking algorithm and the used tracking parameters whether a connection was observed. …”
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ANALYSIS AND ASSESSMENT OF FINANCIAL AND BUSINESS ACTIVITIES TO MINIMIZE TAX RISKS OF COMPANIES by E. V. Lyuter, Y. V. Gusarova, M. M. Starkova, A. Yu. Klonitskaya

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Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned by Marketa Ciharova, Khadicha Amarti, Ward van Breda, Ward van Breda, Martin J. Gevonden, Sina Ghassemi, Annet Kleiboer, Christiaan H. Vinkers, Christiaan H. Vinkers, Christiaan H. Vinkers, Christiaan H. Vinkers, Milou S. C. Sep, Milou S. C. Sep, Milou S. C. Sep, Milou S. C. Sep, Sophia Trofimova, Alexander C. Cooper, Xianhua Peng, Xianhua Peng, Mieke Schulte, Mieke Schulte, Eirini Karyotaki, Eirini Karyotaki, Eirini Karyotaki, Pim Cuijpers, Pim Cuijpers, Pim Cuijpers, Heleen Riper, Heleen Riper

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A public benchmark for human performance in the detection of focal cortical dysplasia by Lennart Walger, Matthias H. Schmitz, Tobias Bauer, David Kügler, Fabiane Schuch, Christophe Arendt, Tobias Baumgartner, Johannes Birkenheier, Valeri Borger, Christoph Endler, Franziska Grau, Christian Immanuel, Markus Kölle, Patrick Kupczyk, Asadeh Lakghomi, Sarah Mackert, Elisabeth Neuhaus, Julia Nordsiek, Anna‐Maria Odenthal, Karmele Olaciregui Dague, Laura Ostermann, Jan Pukropski, Attila Racz, Klaus von derRopp, Frederic Carsten Schmeel, Felix Schrader, Aileen Sitter, Alexander Unruh‐Pinheiro, Marilia Voigt, Martin Vychopen, Philip vonWedel, Randi vonWrede, Ulrike Attenberger, Hartmut Vatter, Alexandra Philipsen, Albert Becker, Martin Reuter, Elke Hattingen, Alexander Radbruch, Rainer Surges, Theodor Rüber

“…The benchmark test set was chosen to consist of 15 subjects most predictive for human performance and 13 subjects identified by at most 3 of the 28 readers. …”
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